Genera, typically hand-in-hand with their branching species, are essential elements of vocabulary-based information constructs, in particular scientific taxonomies. Should they also feature in formal ontologies, the highest of such constructs? I argue in this article that the answer is “Yes” and that the question posed in its title also has a Yes-answer: The way medieval ontologists sliced up the world into genera does matter to formal ontology. More specifically, the way Dietrich of Freiberg, a Latin scholastic, conceived and applied strictly (...) generic criteria to slice up the world into its entities can provide some guidelines to the field of formal ontology with respect to not only its contents, but also its scope. In particular, Dietrich's information criterion plays here a central role. (shrink)

Ontologies are some of the most central constructs in today's large plethora of knowledge technologies, namely in the context of the semantic web. As their coinage indicates, they are direct heirs to the ontological investigations in the long Western philosophical tradition, but it is not easy to make bridges between them. Contemporary ontological commitments often take causality as a central aspect for the ur-segregation of entities, especially in scientific upper ontologies; theories of causality and philosophical ontological investigations often go hand-in-hand, (...) and were essentially inseparable in medieval thought. This constitutes the foundation for a bridge, and this article analyzes the causality-based ontology of the late medieval philosopher Dietrich of Freiberg from the viewpoint of today's upper-ontology engineering. In this bridging attempt, it offers a translation into English of the first part of Dietrich's De origine (abbreviated title) that is a compromise between traditional scholarly translations of medieval Latin philosophical texts and contemporary ontology. (shrink)

A. Newell and H. A. Simon were two of the most influential scientists in the emerging field of artificial intelligence (AI) in the late 1950s through to the early 1990s. This paper reviews their crucial contribution to this field, namely to symbolic AI. This contribution was constituted mostly by their quest for the implementation of general intelligence and (commonsense) knowledge in artificial thinking or reasoning artifacts, a project they shared with many other scientists but that in their case was theoretically (...) based on the idiosyncratic notions of symbol systems and the representational abilities they give rise to, in particular with respect to knowledge. While focusing on the period 1956-1982, this review cites both earlier and later literature and it attempts to make visible their potential relevance to today's greatest unifying AI challenge, to wit, the design of wholly autonomous artificial agents (a.k.a. robots) that are not only rational and ethical, but also self-conscious. (shrink)

The opinion defended in this paper is that the interrelationships between the phenomena of data and information can provide a strong basis for analyzing knowledge as a quantified and qualified construction. As other models (e.g., Augusto’s General Theory of Knowledge) suggest, it is important to distinguish knowledge from both data and information in the complicated trio composed of data, information, and knowledge (DIK). However, data and information can be combined into informative data. Taking into account quantified and qualified informative data, (...) I speak here of quantified and qualified knowledge structures. (shrink)

This article is a knowledge technology case study of DNAOS, a distributed platform for Knowledge Resource Entitlement, Modeling, Management, and Sharing (KREMMS). Some historical aspects of its design, development, and release are briefly discussed, after which the DNAOS technology is commented upon from the specific viewpoint of KREMMS. At the core of this platform is the conception of knowledge as a natural phenomenon, which conception is reflected in the ontology of this technology: Fundamental knowledge structures and structuring principles, believed to (...) be “natural,” including qualification, resources, and relationships, are considered theoretically and modeled computationally. Finally, with the help of images, the reader is briefly introduced to some DNAOS capabilities, touching on transaction, application, data, model, and interface. (shrink)